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9 results for “long-term field studies”
Selection against admixture and gene regulatory divergence in a long-term primate field study
<p><strong>Selection against admixture and gene regulatory divergence in a long-term primate field study</strong><br> <em>Vilgalys & Fogel et al. (bioRxiv)</em></p> <ul> <li><a href="https://zenodo.org/api/files/7cb721ac-b8e0-4dc0-a91b-fd54cc70f8d7/Panubis1.0_to_hg38.chain.gz">Panubis1.0_to_hg38.chain.gz</a>; <a href="https://zenodo.org/api/files/7cb721ac-b8e0-4dc0-a91b-fd54cc70f8d7/hg38_to_Panubis1.0.chain.gz">hg38_to_Panubis1.0.chain.gz</a>: Liftover chain files between Panubis1.0 and hg38. </li> <li><a href="https://zenodo.org/api/files/7cb721ac-b8e0-4dc0-a91b-fd54cc70f8d7/amboseli_LCLAE_tracts.txt.gz">amboseli_LCLAE_tracts.txt.gz</a>: Local ancestry calls for 442 wild, hybrid baboons studied as part of the Amboseli Baboon Research Project. Local ancestry was called using LCLAE and is represented by a 0 for homozygous yellow ancestry, 2 for homozygous anubis ancestry, and 1 for heterozygous ancestry. Each row in the file has a genomic position (chromosome, start, and end), local ancestry call, and the individual for whom the call was made. </li> <li><a href="https://zenodo.org/api/files/7cb721ac-b8e0-4dc0-a91b-fd54cc70f8d7/masked_yellow_and_anubis.vcf.gz?versionId=25e26878-bca3-4667-9668-9e19424bc23e">masked_yellow_and_anubis.vcf.gz</a>: Genotype calls for non-Amboseli yellow and anubis baboons, after masking to remove putative introgressed ancestry. </li> <li>A time-stamped version of the code is included here, and also available on GitHub at <a href="http://github.com/TaurVil/VilgalysFogel_Amboseli_admixture">github.com/TaurVil/VilgalysFogel_Amboseli_admixture</a>. </li> </ul>
Data from: Demographic, behavioral, and ecological data from a long-term field study of wild baboons in Amboseli, Kenya
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Long-term studies of secondary succession and community assembly in the prairie-forest ecotone of eastern Kansas, Old-field succession experiment
Local and regional-scale processes interact to govern the assembly, diversity and functioning of ecological communities. Evaluating the interplay of these differently-scaled processes in the regulation of ecological systems is a challenging problem, but is crucial towards understanding and predicting the potential effects of accelerated human activity on biological diversity and ecosystem sustainability. Since 2000, two long-term field experiments have been underway in grasslands of eastern Kansas to investigate the interplay of soil resource availability, species interactions and regional processes governing plant secondary succession, community assembly, biodiversity, and ecosystem functioning. Both experiments involve manipulations of soil nutrients in permanent grassland study plots and employ multi-species seed addition treatments to evaluate the contribution of dispersal limitation and regional constraints on local species pools to the regulation of plant community dynamics. Old-field succession experiment, previously funded by the National Science Foundation, was initiated in 2001 in a section of the abandoned hay field that was sprayed with herbicide, plowed and disked prior to the start of the study to investigate plant community dynamics in the context of old-field succession initiated on bare soil. The experimental design involves factorial experimental gradients of nitrogen (N) supply (four levels of N fertilization), phosphorus (P) supply (two levels of P fertilization) and plant propagule input achieved by adding seeds of 50+ native and naturalized species to half of the study plots. With annual sampling this experiment allows us to examine old-field succession and community assembly unfolding along gradients of N and P fertilization and under conditions of ambient and experimentally-enriched species pools.
Long-term data from field erosion plot studies in eastern Austria
<p>Long-term runoff plot experiments were conducted at three sites in eastern Austria to evaluate the impact of conservation tillage. Following soil tillage treatments were investigated: 1) conventional tillage with ploughing in fall (CT), 2) mulch tillage with cover crops during winter period (MT), and 3) no tillage with cover crops during winter period (NT). Soil textures range from silt loam to loam.</p> <p>Datasets include for each site and each year the period of operation of the plots, the planted crop, the annual precipitation, surface runoff, soil loss, surface losses of nitrogen, phopshorus and soil organic carbon as well as absolute and relative crop yields.</p>
Long-term data from field erosion plot studies in eastern Austria
<p>Long-term runoff plot experiments were conducted at three sites in eastern Austria to evaluate the impact of conservation tillage. Following soil tillage treatments were investigated: 1) conventional tillage with ploughing in fall (CT), 2) mulch tillage with cover crops during winter period (MT), and 3) no tillage with cover crops during winter period (NT). Soil textures range from silt loam to loam.</p> <p>Datasets include for each site and each year the period of operation of the plots, the planted crop, the annual precipitation, surface runoff, soil loss, surface losses of nitrogen, phopshorus and soil organic carbon as well as absolute and relative crop yields.</p>
Data from: Phenological responses to multiple environmental drivers under climate change: insights from a long-term observational study and a manipulative field experiment
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"Field integration of shoot gas exchange and leaf chlorophyll fluorescence measurements to study the long-term regulation of photosynthesis in situ" data set
<p>The main data used in the "Field integration of shoot gas exchange and leaf chlorophyll fluorescence measurements to study the long-term regulation of photosynthesis in situ" publication, as well as the readme-file for the dataset. Supplementary figures are available at the Tree Physiology website.</p>
Data from: Who escapes detection? Quantifying the causes and consequences of sampling biases in a long-term field study
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Long-term data from field erosion plot studies in eastern Austria
<p>The data include measured data for three different soil tillage practices from three experimental sites in eastern Austria. The Tables 1-3 include for each site and each year the period of operation, the planted crop, the annual precipitation, the surface runoff in mm, the soil loss in t/ha and the surface losses of total nitrogen, total phosphorus and soil organic carbon in kg/ha. Crop yields were determined from 45 m² large plots with one or two replications. Yields in kg/ha are not available for all years, but relative yield in % are.</p> <p>The experiments were conducted at three sites in eastern Austria: in Mistelbach, Pixendorf and Pyhra. The soils in Mistelbach and Pyhra are classified as Typic Argiudolls while the soil in Pixendorf is an Entic Hapludoll. Soil textures range from silt loam to loam. Average annual rainfall (1994-2018) at the sites amounts from 621 to 916 mm with average annual air temperatures between 9.4 and 10.4 °C.</p> <p>Following soil tillage treatments were investigated: (1) conventional tillage system with ploughing in fall (CT), (2) mulch tillage with cover crops during winter (MT) and (3) no-till with cover crops during winter (NT). The study design was a randomized block and each treatment was replicated twice. Each treatment was equipped with one field runoff plot. The experimental plots were 6 m wide and – depending on site conditions - between 40 and 80 m long. The study design consisted of 3 (Mistelbach) and 4 m wide (Pixendorf, Pyhra) and 15 m long runoff plots for each management variation. Each plot was bordered by stainless steel metal sheets. At the lower end of the plot surface runoff and soil loss were collected in a trough and then diverted by a 100-mm PVC pipe to an Automated Erosion Wheel (AEW). The design of this AEW is similar to a tipping bucket and consists of four equal sections of five liters resulting in a resolution of each tip of 0.08 mm for 60 m² plots. A magnetic sensor system was used for continuous runoff measurement.</p> <p>Soil-water-suspension was divided by an adapted multi-tube divisor taking 3.3% of the sample that is collected in a 60 L collection tank. After each erosive storm the collection tank was emptied and the runoff sample was brought to the laboratory, weighed and dried until constant mass was achieved to determine sediment concentration. Based on the continuously measured runoff data from the data logging system and the sediment concentration the amount of soil loss from the plots was calculated for each erosive event.</p> <p>Throughout the investigation period soil erosion, surface runoff and nutrient and carbon losses and partly also pesticide losses due to erosion processes were determined for all sites and tillage systems. Immediately after planting/seeding of summer crops the erosion plots were installed and then operated until harvest. After the harvest the equipment was removed. No measurements were performed during winter due to limited accessibility and frost damages to the equipment. At each site an automatic tipping bucket rain gauge was placed to measure rainfall in 5-min intervals.</p> <p>Crop yield was determined from each treatment with three replications.</p> <p>Total nitrogen and total carbon in sediment samples was analysed by dry combustion [3](OeNorm L1080, 1989) using a C/N Analyzer (Vario Max CN, Elementar). Soil organic carbon content was obtained by subtracting inorganic carbon content measured volumetrically by the Scheibler method with a Calcimeter (OeNorm L1084, 1989). Total phosphorus of the sediment was determined using a UV/VIS spectral photometer (DU-640 Beckmann).</p> <p>Pesticides were extracted from water by solid phase extraction and from sediments using distilled water or organic solvent [6]. After shaking for several hours and centrifugation, the sample passed through a solid phase extraction. After evaporation of the extract the pesticide residues were redissolved in another solvent and analysed with high performance liquid chromatography (HPLC).</p>
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International Brain Laboratory public data
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OpenNeuro
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